A Genetic Algorithm Based Architecture for Evolving Type-2 Fuzzy Logic Controllers for Real World Autonomous Mobile Robots
A Genetic Algorithm Based Architecture for Evolving Type-2 Fuzzy Logic Controllers for Real World Autonomous Mobile Robots
复制标题
一种基于遗传算法的架构，用于演进现实世界自主移动机器人的 2 型模糊逻辑控制器
DOI：
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发表时间：
2007
期刊：
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通讯作者：
H. Hagras
中科院分区：
文献类型：
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作者：
Christian Wagner;H. Hagras
2型模糊逻辑控制器（FLC）已经开始出现作为一个有前途的控制机制，自主移动的机器人在真实的世界环境中导航。这是因为这样的机器人需要控制机制，如2型FLC，它可以处理大量的不确定性存在于真实的世界环境。然而，手动设计和调整用于间隔2型FLC的2型隶属函数（MF）以给出良好的响应是一项困难的任务。本文将提出一种基于遗传算法（GA）的体系结构，以发展类型2 MF的间隔类型2 FLC的移动的机器人，将在真实的世界环境中导航。基于GA的系统收敛后，少量的迭代类型2 MF，这给出了一个非常好的性能。我们已经进行了一系列的真实的世界的实验中，进化的2型FLC控制一个真实的机器人在室外竞技场。进化的2型FLC处理了真实的世界中存在的不确定性，从而提供了非常好的性能，其性能优于1型FLC以及手动设计的2型FLC。
The type-2 Fuzzy Logic Controller (FLC) has started to emerge as a promising control mechanism for autonomous mobile robots navigating in real world environments. This is because such robots need control mechanisms such as type-2 FLCs which can handle the large amounts of uncertainties present in real world environments. However, manually designing and tuning the type-2 Membership Functions (MFs) for an interval type-2 FLC to give a good response is a difficult task. This paper will present a Genetic Algorithm (GA) based architecture to evolve the type-2 MFs of interval type-2 FLCs for mobile robots that will navigate in real world environments. The GA based system converges after a small number of iterations to type-2 MFs which give a very good performance. We have performed a series of real world experiments in which the evolved type-2 FLCs controlled a real robot in an outdoor arena. The evolved type-2 FLCs dealt with the uncertainties present in the real world to give a very good performance that has outperformed their type-1 counterparts as well as the manually designed type-2 FLCs.